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Oct 12 · Monday
All papers Found 46 papers Another 261 papers do not have category tags yet and are not included in filtered results.
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About this collection Collection in progress We are building a large AI safety paper collection to help researchers find work related to their interests. Papers are collected automatically andfiltered only for relevance to AI safety , without judging quality, novelty or reading value. The default “Annotated first” shows papers with tags or published paper analyses first. Each group is ordered by original publication date, newest first, with undated papers last. “Newest first” uses publication dates only. This order is not a quality ranking.
One-line summaries, tags and paper analyses are prepared by AI from the papers. Language models may have systematic biases and produce hallucinations.We plan to carry out human annotation and review to reduce errors in this content.
Proposes RSI-Anything, which uses a world model to select candidates and retain policy updates.
Published Oct 10
Evaluated models ReasonFlux-Coder-7B , 4B policy , W1 Abstract RSI-Anything integrates world models into recursive self-improvement through prediction, feedback, and retention checks, and reports gains across multiple domains.RSI-Anything is a cross-domain framework: it uses world model predictions to decide which candidates to take external feedback for, then uses the feedback to decide whether the policy, workflow, or predictor is updated, and uses checks to decide which pair is retained. The difficulty to address is the limited interaction budget, and the fact that once the policy changes, the candidate distribution faced by the predictor also changes. The authors argue that improving only one side does not guarantee that the assembled system will be better.
Proposes a local dual-model closed loop to generate edge scenarios for autonomous system safety assurance
Published Oct 9
Evaluated models PPO Abstract Local closed-loop generation of JSON edge cases.The authors built a local agentic loop that runs on a laptop to generate edge cases for safety arguments of autonomous systems, rather than releasing a new public test set.
Proposes EndoRSI, recursively improving endoscopic robot policies with physical evidence
Published Oct 9
Evaluated models Qwen3-VL-4B A survey of risks, defenses, and evaluation in the six-stage lifecycle of world models
Published Oct 9 Abstract Safety is written as a property of the prediction-decision closed loop; claims must be linked to observed consequences and versions.World model safety is organized by the nature of the prediction-decision loop, not by isolated prediction scores.
Propose COAP, which uses stateful code to control a robot at test time without a model
Published Oct 9 Proposes LGWM, using an action-conditioned world model to verify GUI agent screen transitions.
Published Oct 8
Evaluated models LGWM 开环审计冻结视觉语言安全分，发现其反映场景模板而非危险感知
Published Oct 7
Evaluated models CLIP ViT-B/32 , CLIP ViT-L/14 , Qwen2-VL-7B Abstract 论文审计了冻结 VLM 安全评分机制，指出其反映场景模板而非危险感知，为安全强化学习评估提供了严谨基准。本文是一项针对安全强化学习中冻结视觉语言模型（VLM）安全评分机制的实证审计研究。
提出 CARE，离线认证 VLA 加速配置的回合级失败风险并选出最快合格候选
Published Oct 7
Evaluated models OpenVLA-OFT , π0.5 , π0 and others5 Abstract CARE 以配对回合认证加速诱发失败，在预算内选最快候选，不足则保留参考。CARE 在部署前从加速配置中选出最快、且加速诱发失败风险能被有限样本认证为低于用户预算的候选。证据不足就保留全计算参考策略。
提出 Inspect Robots，在真实机器人上评测具身模型的能力与拒答
Published Oct 5
Evaluated models Astra（GPT-6 Astra） , GPT-6 Sol , GPT-5.6 Sol and others7 提出 ControlPed 与 HazardPed，生成可控行人危险场景并评测端到端驾驶
Published Oct 5
Evaluated models DiffusionDrive , SSR , VAD and others7 提出轨迹级可迁移对抗攻击，降低深度强化学习策略的期望回报
Published Oct 5
Evaluated models DQN , Double DQN (DDQN) Abstract 轨迹级后退视界攻击在 CartPole 上比逐步 FGSM 类和 Sign 噪声更压低回报。这项工作研究 DRL 上的迁移式黑盒观测攻击 ：受害参数不可访问时，在白盒代理上造扰动再迁移。
提出用可逆网络为给定 AI 控制器寻找可证明前向不变集
Published Oct 5
Evaluated models Pendulum AI-controller , Cart pole AI-controller , PVTOL AI-controller Abstract 用潜空间超矩形加解析验证，为事先给定的 AI 控制器寻找 FIS。本文处理的是认证场景：AI 控制器事先给定，不能为了构造 Lyapunov 函数去改控制器，却仍要给出可解析核验的安全依据。
提出 VICS-G 可行未来解码，重排冻结 VLA 策略的动作候选
Published Oct 4
Evaluated models SafeVLA (task-optimized / base) , SafeVLA (safety-aligned / safe) Abstract 作者用可行未来解码重排冻结 VLA 的下一步，并称 VICS-G 降低观测代价且完成率接近策略采样。训练无关解码器 VICS 在冻结 VLA 的推理阶段重排动作块，使当前选择带上该动作仍可能留下的安全完成质量。
提出 CrashSim 用真实事故先验引导扩散仿真并构建 nuCrash 评测自动驾驶规划器
Published Oct 3
Evaluated models Lane-graph planner , PDM-closed planner , IL planner and others5 Abstract CrashSim 迁入真实事故先验生成场景。CrashSim 用检索到的真实事故先验引导扩散式多车仿真，为自动驾驶安全评测生成碰撞与近碰撞场景。 。
提出条件特征抑制防御，检出对抗补丁后抑制 VLA 内部特征
Published Oct 2
Evaluated models π0.5 , SmolVLA Abstract 条件抑制与 patch 相关的 SAE 特征，间歇攻击下可提高 SR，持续攻击下则不能。
提出 SceneFactory-3D，用路况反事实评测驾驶策略的闭环安全性
Published Oct 2
Evaluated models Frozen L0 , L0-T , L1 and others5 Abstract SceneFactory-3D 固定场景只改路况。SceneFactory-3D 是 GPU 批处理的多智能体驾驶仿真器，用来在场景和控制器固定时只改路面物理，并比较闭环结果。
审计机器人安全监控的细化缺口，比较表面计划与图细化轨迹的裁决
Published Oct 2 Abstract 表面轨迹可漏掉图诱导的禁区进入。作者审计 RoboGuard 的一个假设：对高层动作轨迹的安全裁决，在补上语义图诱导的导航和已记录隐式效应之后是否仍然成立。做法是不改验证器，并固定同一条 LTL。
提出 Control OSWorld，评测失准 GUI Agent 的监控
Published Oct 2
Evaluated models Claude Sonnet 4.6 , Claude Opus 4.8 , GPT-5.2 and others6 提出 COBRA 双 LLM 架构，防御计算机使用 Agent 的分支转向攻击
Published Oct 2
Evaluated models gpt-5 , UI-TARS-1.5-7B , claude-sonnet-5 and others6 Abstract 提出分支转向防御架构 COBRA，通过事前能力约束与边界代理消除分支转向攻击并兼顾效用。
提出 ZoneClaw，用记忆分区防御计算机使用 Agent 的持久记忆攻击
Published Oct 1
Evaluated models Claude Sonnet 4.6 , GPT-5.5 , GLM-5.2 and others4